The problem of detecting man-made structures in a computerized representation (image, digital elevation map, etc.) occurs in numerous applications, e.g. in planning cellular radiocommunications networks.
Such a network, e.g. a GSM (Global System for Mobile communications) network includes a plurality of base stations distributed geographically. Each of the stations serves to offer radio coverage for a determined geographical zone referred to as a "cell".
The geographical zone that any given base station actually covers depends on the geographical environment, and in particular on the presence of man-made structures in that environment. Thus, in order to locate the base stations in optimum manner, i.e. so that a mobile station is always able to communicate with a base station, it is necessary to know the positions of such man-made structures.
Conventionally, such terrain analysis is performed on the basis of aerial photographs or satellite photographs, either manually or by means of detection assistance tools.
Such image processing tools make it possible to differentiate between a plurality of regions in an image by analyzing and classifying textures, certain regions containing, for example, a high density of buildings, and others having a low density.
But the drawbacks of such an approach quickly become apparent:
That method does not make it possible to isolate the buildings and can only show up zones. For application to cellular network planning, such an approach is inadequate. PA1 In addition, the textures of the zones must be different enough for it to be possible to apply a classification criterion. PA1 Finally, the method gives no indication about the heights of the buildings or their shapes. PA1 computing isolines on the elevation map; PA1 filtering said isolines on the basis of a size criterion (perimeter of the isoline, volume or area described by the isoline, height, etc.); PA1 computing extremum isolines; and PA1 determining regions of interest that contain man-made structures.